Abstract
We present the fusion of simple retrieval strategies with thesaural resources to perform document and query translation by text categorisation for cross–language retrieval in a collection of medical images with case notes. The collection includes documents in French, English and German. The fusion of visual and textual content is also treated. Unlike most automatic categorisation systems our approach can be applied with any controlled vocabulary and does not require training data. For the experiments we use Medical Subject Headings (MeSH), a terminology maintained by the National Library of Medicine existing in 12 languages. The idea is to annotate every text of the collection (documents and queries) with a set of MeSH terms using our automatic text categoriser. Our results confirm that such an approach is competitive. Simple linear approaches were used to combine text and visual features.
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Gobeill, J., Müller, H., Ruch, P. (2007). Translation by Text Categorisation: Medical Image Retrieval in ImageCLEFmed 2006. In: Peters, C., et al. Evaluation of Multilingual and Multi-modal Information Retrieval. CLEF 2006. Lecture Notes in Computer Science, vol 4730. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74999-8_88
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DOI: https://doi.org/10.1007/978-3-540-74999-8_88
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74998-1
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